GitHub

Rust-first Mermaid-compatible diagram engine with smarter parsing, deterministic layouts, and high-quality output across CLI, SVG, terminal, and WASM targets

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IEEE

Semantic Encoding Supervises LiDAR Semantic Segmentation

Abstract: Semantic segmentation using LiDAR is a fundamental aspect in perception for autonomous driving. Conventional training methodologies commonly employ one-hot encoding for labels, followed by a ...
eLife

Semantical and Geometrical Protein Encoding Toward Enhanced Bioactivity and Thermostability

ProtSSN is a valuable approach that generates protein embeddings by integrating sequence and structural information, demonstrating improved prediction of mutation effects on thermostability compared ...
ascopubs.org

PROTA: A phase I clinical trial combining an oncolytic adenovirus encoding for TNFa and IL-2 with pembrolizumab for the treatment of platinum-resistant or -refractory ovarian ...

Characterizing FOLR1 expression in low-grade serous ovarian carcinoma. This is an ASCO Meeting Abstract from the 2024 ASCO Annual Meeting I. This abstract does not include a full text component.
IEEE

Enhancing Context Models for Point Cloud Geometry Compression With Context Feature Residuals and Multi-Loss

Abstract: In point cloud geometry compression, context models usually use the one-hot encoding of node occupancy as the label, and the cross-entropy between the one-hot encoding and the probability ...
Hacker

The Concept Behind "Mean Target Encoding" in AI & ML

Categorical Encoding - Undoubtedly, is an integral part of data pre-processing in machine learning. Although the most common categorical encoding techniques are Label and One-Hot encoding, there are a ...